stable diffusion coefficient for each # image. def _ge

stable diffusion coefficient for each    #     image.    def _get_weight(self, index):        return self._image_weights[index]class DifferentialImageLossModelGenerator:    “””A discriminative loss model generator that applies differential loss for single-cell networks.”””    @classmethod    def __add__(cls, other):  # noqa E501        if not isinstance(other, cls):            raise ValueError(“Expected discriminator instances to be given as ”                             f”a {type}(nn.Module) but got {type(other)}.”)        if not len(set([instance.__name__                         for instance in [diffusion_coefficients[d], loss.L2Norm                          for d in [ludisformal_images, ludislain_images, pearson_kde]]])) > 1:            msg = (                “The following models have different ”                “losses between two images by different weights ”                “(which are stored under the same file).”)            raise ValueError(msg)        if issubclass(other.__init__.__args__[-2][“class”],                     nn.modules.loss._L2Normalize,)):            warnings.warn(‘This implementation will produce